Method and device for in-home sleep and signal analysis

ABSTRACT

The present invention provides a method of conducting a sleep analysis by collecting physiologic and kinetic data from a subject, preferably via a wireless in-home data acquisition system, while the subject attempts to sleep at home. The sleep analysis, including clinical and research sleep studies and cardiorespiratory studies, can be used in the diagnosis of sleeping disorders and other diseases or conditions with sleep signatures, such as Parkinson&#39;s, epilepsy, chronic heart failure, chronic obstructive pulmonary disorder, or other neurological, cardiac, pulmonary, or muscular disorders. The method of the present invention can also be used to determine if environmental factors at the subject&#39;s home are preventing restorative sleep.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority as a continuation of U.S. patentapplication Ser. No. 17/346,640, which was filed on Jun. 14, 2021 andwhich is a continuation of U.S. patent application Ser. No. 17/145,661,which was filed on Jan. 11, 2021, issued as U.S. Pat. No. 11,064,937 onJul. 20, 2021, and which is a continuation of U.S. patent applicationSer. No. 16/233,520, which was filed on Dec. 27, 2018, issued as U.S.Pat. No. 10,925,535 on Feb. 23, 2021, and which is a continuation ofU.S. patent application Ser. No. 15/229,242, which was filed on Aug. 5,2016 and which issued as U.S. Pat. No. 10,426,399 on Oct. 1, 2019, andwhich is a continuation of U.S. patent application Ser. No. 11/811,156filed on Jun. 8, 2007. The specifications and drawings of each of theabove patents and applications are hereby incorporated by reference intheir entirety.

The U.S. Government has a paid-up license in this invention and theright in limited circumstances to require the patent owner to licenseothers on reasonable terms provided for by the terms of grant numbers2R44NS042451-04 and 5R44NS042451-03 awarded by the National Institutesof Health.

BACKGROUND OF THE INVENTION

Nearly one in seven people in the United States suffer from some type ofchronic sleep disorder, and only 50% of people are estimated to get therecommended seven to eight hours of sleep each night. It is furtherestimated that sleep deprivation and its associated medical and socialcosts (loss of productivity, industrial accidents, etc.) exceed $150billion dollars per year. Excessive sleepiness can deteriorate thequality of life and is a major cause of morbidity and mortality due toits role in industrial and transportation accidents. Sleepiness furtherhas undesirable effects on motor vehicle driving, employment, higherearning and job promotion opportunities, education, recreation, andpersonal life.

Primary sleep disorders affect approximately 50 million Americans of allages and include narcolepsy, restless legs/periodic leg movement,insomnia, and most commonly, obstructive sleep apnea (OSA). OSA'sprevalence in society is comparable with diabetes, asthma, and thelifetime risk of colon cancer. OSA is grossly under diagnosed; anestimated 80-90% of persons afflicted have not received a clinicaldiagnosis. Secondary sleep disorders include loss of sleep due to painassociated with chronic infections, neurological/psychiatric disorders,or alcohol/substance abuse disorders.

Sleeping disorders are currently diagnosed by two general methods.Subjective methods, such as the Epworth and Standford Sleepiness Scale,generally involve questionnaires that require patients to answer aseries of qualitative questions regarding their sleepiness during theday. With these subjective methods, however, it is found that thepatients usually underestimate their level of sleepiness or theydeliberately falsify their responses because of their concern regardingpunitive action or as an effort to obtain restricted stimulantmedication.

The second group of methods uses physiological evaluations, such asall-night polysomnography to evaluate a patient's sleep architecture(e.g., obtaining respiratory disturbance index to diagnose sleep apnea).A polysomnogram (PSG) can also be followed by an all-day test such asthe Multiple Sleep Latency Test (MSLT) or its modified version, theMaintenance of Wakefulness Test (MWT). The PSG typically requirespatients to spend the night in a sleep laboratory connected to multiplesensors while they attempt to sleep. Because it is conducted in a labsetting, a PSG cannot provide information about a patient's sleepingenvironment, such as noise, light, or allergens. A PSG also can bedifficult to conduct because of a patient's travel concerns or anxietyrelated to sleeping away from home. Many patients also exhibit a “firstnight effect” related to a change in sleeping environment. The firstnight effect often requires a second night in the sleep lab to obtainaccurate results. Therefore, the first night effect can easily doublethe cost of conducting a PSG in a sleep lab.

To combat the difficulties of conducting a PSG in a sleep lab, variousmethods have been employed to attempt to conduct a PSG test in apatient's home. The systems used in these methods have not been capableof transmitting data. Therefore, these systems have only allowedunattended PSG tests. These methods involve storage of the data to acomputer hard disc or other media for the duration of the test. Afterthe test is completed, the media is received, read, and analyzed.Obtaining the data creates an additional delay between completion of thetest and the final diagnosis that is not present for a lab-based PSG.Further, unattended tests are plagued with signal failure. In one studyinvolving unattended home PSG, data from over 23% of the patients wereunusable due to missing channels, even though a technician called thePSG recording device every 30 minutes to check the quality of therecordings.

None of the current methods for conducting a PSG at home allowtransmission of the collected data during the test. All of the currentmethods require the PSG data to be stored during the test and read onlyafter the test has been completed. As such, the data cannot beperiodically or continuously checked for adequacy. Even if the data wereperiodically evaluated, the current methods do not use a step ofallowing a remote monitor to communicate with the subject to correct anysensor/signal problems. The current methods also do not include livevideo feeds, enabling a remote monitor to visualize the subject duringthe test. Because of the lack of data availability, communication, andvideo, the current methods of conducting a PSG at home are by definitionunattended sleep studies. It is therefore an object of the presentinvention to provide a method of conducting a sleep analysis at homewherein the data is transmitted at substantially the same time it thatis collected or created. It is another object of the present inventionto provide a method of conducting a sleep analysis at home that isremotely attended. It is another object of the present invention toprovide a method of conducting a sleep analysis that includesinformation about the patient's sleeping environment, includingenvironmental factors. It is still another object of the presentinvention that this method of conducting a sleep analysis beinexpensive.

SUMMARY OF THE INVENTION

The present invention provides a method of conducting a sleep analysisby collecting physiologic and kinetic data from a subject, preferablyvia a wireless in-home data acquisition system, while the subjectattempts to sleep at home. The sleep analysis, including clinical andresearch sleep studies and cardiorespiratory studies, can be used in thediagnosis of sleeping disorders and other diseases or conditions withsleep signatures, such as Parkinson's, epilepsy, chronic heart failure,chronic obstructive pulmonary disorder, or other neurological, cardiac,pulmonary, or muscular disorders. The method of the present inventioncan also be used to determine if environmental factors at the subject'shome are preventing restorative sleep.

The method of conducting a sleep study at home includes a number ofsteps that enhance this method over other methods presently used. Thesefeatures available in various embodiments of the present invention mayinclude, but are not necessarily limited to: a step for hooking up thepatient with the necessary sensors at the doctor's office or the home, astep for collecting multiple channels of data to evaluate a number ofphysiological, kinetic, and environmental features of the subject andsleeping location; a step for including a subject's body motion; a stepfor using removable memory for data buffering and storage; a step formovement artifact correction using video; a step for transmitting datawirelessly to a remote processing or monitoring station after a manualor automatic radio frequency (RF) sweep; a step for remotely checkingthe data for adequacy; a step for remotely monitoring the subject viastreaming data and audio/video for the duration of the test; a step forcommunicating with the subject during the test; and a step for adjustingelectrodes and other sensors during the test.

The software used in various steps of the present invention allows thein-home data acquisition system to perform a number of operations thatother systems cannot accomplish with the same type of hardware. The useof software filtering allows determination of airflow, tidal volume,ventilation rate, and snore detection from a single pressure transducer.The use of software also makes many of the video-related featurespossible. Software is used to synchronize video with the other signalsfor display. Software is also used to remove data artifacts created bysubject movement. The software corrects motion artifacts by using dataacquired from accelerometers and video.

The present invention may include a step of transmitting data via awired network such as a dial-up modem, cellular networks, digitalsubscriber lines (DSL), cable broadband, fiber-optic lines, satellitecommunications, direct radio, infra-red links, and the like. The datacan be transmitted once, at multiple points during the test, orcontinuously. With continuous data transmission, the sleep test can beremotely monitored from anywhere around the world. The data furthermoremay be monitored by multiple viewing stations by methods including butnot limited to serial retransmission from one station to another, orsimultaneous transmission by 3-way or conference calling, broadcastingor the like. The data from the acquisition system is available forremote monitoring in real time, it can be saved and scored later, or maybe quantitatively analyzed and scored (even automatically) and thenviewed. With automatic or computer-assisted scoring, the software canalert a individual performing remote monitoring when a physiologicalevent (such as a drop in oxygen saturation) or a technological event(such as an electrode becoming disconnected) occurs.

Various embodiments of the present invention include the step ofapplying at least two sensors to the subject. The sensors can be appliedat any location, such as a physician's office or place of business, orthe subject's home or other sleeping location. The subject's sleepinglocation includes but is not limited to the subject's home, apartment,or the like, as well as a hotel, nursing home, or other location wherean individual could sleep and where this analysis could be done morecontrollably and/or less expensively than in an attended sleep lab orhospital setting. Similarly, the sensors can be applied by a variety ofindividuals, including but not limited to a physician, nurse, sleeptechnician, or other healthcare professional. Just as preferably, thesensors could be applied by the subject or the subject's spouse, friend,roommate, or other individual capable of attaching the various sensorswith guidance and instruction.

In one embodiment, the present invention includes the steps of applyingtwo or more sensors to a subject; connecting the sensors to an in-homedata acquisition system capable of transmitting the signals from thesensors or retransmitting a signal based at least in part on at leastone of the signals from the sensors; collecting signals from the sensorswhile the subject attempts to sleep at home; and analyzing the signalsto determine whether the subject has a sleeping disorder. The first andsecond steps of this (and every other) embodiment can also be switched,meaning the sensors are connected to the in-home data acquisition systemand then applied to the subject. The step of collecting data while thesubject attempts to sleep allows for diagnosis of insomnias in additionto parasomnias and other conditions that manifest while the subjectactually sleeps. Further, it is understood that the first step of thepresent invention involving applying two or more sensors to a subjectcan be accomplished by applying any combination of sensors, includingtwo or more EEG electrodes.

Another embodiment of the present invention includes the steps ofapplying two or more sensors to a subject; connecting the sensors to anin-home data acquisition system; collecting signals from the sensorswhile the subject attempts to sleep at home; storing the signals onremovable memory; retrieving the signals; and analyzing the signals todetermine whether the subject has a sleeping disorder. The steps ofstoring and retrieving the signals allow the analysis to be completed ata convenient time, rather than requiring analysis as the data iscollected. These steps also allow the in-home data acquisition system tobe reused after the data is removed with the removable memory, even ifthe data has not been viewed or analyzed.

In another embodiment, the present invention includes the steps ofapplying two or more sensors to a subject; connecting the sensors to anin-home data acquisition system; collecting signals from the sensorswhile the subject attempts to sleep at home; pre-processing the signals,for example to remove motion artifacts, and thereby creating a newsignal or signals; and analyzing the original signals and/or the newsignals to determine whether the subject has a sleeping disorder. Thestep of pre-processing the signals to remove motion artifacts improvesthe quality of the data. For example, the presence of motion artifactcan result in misdiagnosis, prolong procedure duration, and lead todelayed or inappropriate treatment decisions. Thus, it is imperative toremove motion artifacts from the biopotential signal to prevent theseproblems from occurring during the sleep analysis.

In another embodiment, the present invention includes the steps ofapplying two or more sensors to a subject; setting up a video camera inthe subject's sleeping location; connecting the sensors and camera to anin-home data acquisition system; collecting signals from the sensors andcamera while the subject attempts to sleep at home; and analyzing datato determine whether the subject has a sleeping disorder. The step ofusing a video camera allows for monitoring and analysis of the subject'senvironment. For example, the use of video can indicate that thesubject's complaints may be related to changes in light levels, sleepingdisorders of the subject's bedmate, frequent tossing and turningindicative of an unsuitable mattress, coughing or sneezing indicative ofpoor air quality or the presence of allergens, pets sleeping with thesubject, and the like.

In another embodiment, the present invention includes the steps ofapplying a set of sensors to a subject, the sensors being for twoelectroencephalogram (EEG) channels, two electro-oculogram (EOG)channels, one chin electromyogram (EMG) channel, one nasal airflowchannel, one oral airflow channel, two electrocardiogram (ECG) channels,one thoracic respiratory effort channel, one abdominal respiratoryeffort channel, one pulse oximetry channel, one leg EMG channel, and oneaccelerometer; connecting the sensors to a wireless in-home dataacquisition system; collecting signals from the applied sensors and fromadditional environmental sensors while the subject attempts to sleep,the environmental sensors being a digital infrared video camera, anambient light sensor, and an audio channel; pre-processing the signals,for example to remove motion artifacts and to derive a snore signal;using removable memory as a buffer to wirelessly transmit the data to aremote monitoring and/or remote analysis location; evaluating the datato determine if it is adequate for later diagnosis; storing the data ona removable memory card; conducting an RF sweep; wirelessly andcontinuously transmitting all the data from the physiologic, kinetic,and environmental sensors to a remote monitoring location; continuouslymonitoring the subject from the remote monitoring location using thecontinuously transmitted data, including the video feed; contacting thesubject to make any necessary changes to the test, including but notlimited to waking the patient, asking the patient to adjust sensors,altering the type of sleep test to focus on certain channels, orstopping the test; using the video channel to process the data, forexample to remove motion artifacts in the collected signals; andanalyzing the data to determine whether the subject has a sleepingdisorder. This embodiment allows for conducting a complete polysomnogram(PSG) with additional environmental signals that is virtually orremotely attended. This embodiment allows replication of a sleep lab PSGwith the subject comfortably at home. Allowing the subject to attempt tosleep at home eliminates the “first night effect” and provides moreaccurate data for the sleep diagnosis because the home PSG methodcontrols for the subject's sleeping environment. Subjects are alsogenerally more comfortable sleeping at home and are more willing toparticipate in full PSG studies that do not involve traveling to a sleeplab or sleeping in a new environment.

In yet another embodiment, the present invention includes the steps ofproviding a subject with a kit of sensors, an in-home data acquisitionsystem, and instructions; sending the subject home; having the subjectuse the instructions and/or live help (ex., telephone orvideoconferencing assistance) to apply the physiologic and kineticsensors, set up any environmental sensors, and connect all the sensorsto the in-home data acquisition system; collecting some preliminary datafrom the subject; wirelessly transmitting the preliminary data to aremote monitoring or analysis location; evaluating the data to determineif it is adequate for later diagnosis; optionally instructing thesubject to adjust any sensors to obtain adequate data; collectingsignals from the sensors while the subject attempts to sleep at home;wirelessly transmitting all the data to a remote monitoring location;continuously monitoring the subject from the remote monitoring location;and analyzing the data to determine whether the subject has a sleepingdisorder. The step of providing the subject with a kit of sensors, anin-home data acquisition system, and instructions, as well as the stepof having the subject set up the system at home with the availability oflive assistance, allows the subject to participate in a sleep studywithout ever leaving home. This embodiment is particularly useful forhomebound individuals, or individuals who live too far away from a sleepstudy facility.

In still a further embodiment, the present invention includes the stepsof applying two or more sensors to a subject; connecting the sensors toan in-home data acquisition system; collecting signals from the sensorswhile the subject attempts to sleep at home; pre-processing the signals,for example to apply a filter or remove motion artifacts; transmittingthe pre-processed physiological signal at least in part wirelessly to aremote monitor or processor; and analyzing the data to determine whetherthe subject has a sleep disorder.

In still a further embodiment, the present invention includes the stepsof applying two or more sensors to a subject; connecting the sensors toan in-home data acquisition system; collecting signals from the sensorswhile the subject attempts to sleep at home; filtering the physiologicalsignal; transmitting the filtered physiological signal wirelessly to abase station; retransmitting the filtered physiological signal from thebase station to a remote monitor or processor over telephone lines,fiber optic cable, cable broadband, satellite communications, and/or acellular tower; and analyzing the data to determine whether the subjecthas a sleep disorder.

In still a further embodiment, the present invention includes the stepsof applying two or more sensors to a subject; connecting the sensors toan in-home data acquisition system; collecting signals from the sensorswhile the subject attempts to sleep at home; transmitting to anotherlocation the signals or another signal based at least in part on atleast one of the signals from the sensors applied to the subject at asubstantially same time as the signals are received or created; andanalyzing the data to determine whether the subject has a sleepdisorder. The step of transmitting or retransmitting the signals at asubstantially same time allows real-time analysis of the data, ratherthan waiting for the conclusion of the test in order to begin dataanalysis. Real-time analysis also enables the individual performingremote monitoring and analysis to recognize a physiological event (suchas a drop in oxygen saturation, seizure activity, changes in heart rate,and the like) or a technological event (such as an electrode becomingdisconnected, inappropriate movement of a sensor, and the like) occurs.

In still a further embodiment, the present invention includes the stepsof applying two or more sensors to a subject; connecting the sensors toan in-home data acquisition system; collecting signals from the sensorswhile the subject attempts to sleep at home; maintaining theavailability of communication between the subject and a remote monitorfor the duration of the test; and analyzing the data to determinewhether the subject has a sleep disorder.

Additional features and advantages of the invention will be set forth inthe detailed description that follows, and in part will be readilyapparent to those skilled in the art from that description or recognizedby practicing the invention as described herein, including the detaileddescription that follows, the claims, as well as the appended drawings.

It is to be understood that both the foregoing general description andthe following detailed description are merely exemplary of theinvention, and are intended to provide an overview or framework forunderstanding the nature and character of the invention as it isclaimed. The accompanying drawings are included to provide a furtherunderstanding of the invention, and are incorporated in and constitute apart of this specification. The drawings illustrate various embodimentsof the invention and together with the description serve to explain theprinciples and operation of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 Block diagram of one embodiment of the present invention showingthe steps of checking the adequacy of signals and communicating with thesubject.

FIG. 2 Signal flow diagram of one embodiment of the present inventionshowing the in-home data acquisition system.

FIG. 3 Schematic representation of one embodiment of the presentinvention showing the remote data acquisition method.

FIG. 4 Schematic representation of one embodiment of the presentinvention used with a subject to acquire EEG signals from the subjectand then transmit them to the receiver and attached computer.

FIG. 5 Block diagram of one embodiment of the signal processing step ofthe present invention.

FIG. 6 Block diagram of one embodiment of the base station used in thepresent invention.

FIG. 7 Schematic representation of one embodiment of the presentinvention showing an in-home data acquisition system of multipleinterface boxes used on a single subject, wherein the interface boxesare transmitting to a single receiver.

FIG. 8 Block diagram of one embodiment of the present invention showingthe motion artifact rejection process.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention is related to a method of home sleep and signalanalysis, particularly electroencephalogram (EEG) signal analysis. Thepresent invention is further related to the devices used in executingthe method. The present invention includes various embodiments of amethod of home sleep analysis. These embodiments include but are notlimited to one or more of the following steps.

Various embodiments of the present invention include a step fordetermining whether the subject being analyzed for a sleep disordermaintained a normal sleeping pattern prior to the analysis. This stepcan be performed or accomplished a number of ways. In the simplest form,the subject can be questioned regarding his or her previous sleeppatterns. In a somewhat more complex form the subject can be requestedto fill out a questionnaire, which then can be graded to determinewhether his or her previous sleep patterns where normal (or appearednormal). In an even more complex form the subject might undergo allnight polysomnography to evaluate the subject's sleep architecture(e.g., obtaining respiratory disturbance index to diagnose sleep apnea).One of the objectives of this step is to ensure that the results of thesubject's brain wave analysis are not the result of or affected by thesubject's previous environmental factors i.e., intentional lack ofsleep, etc. It is clear that there are numerous ways beyond thoseexamples previously mentioned of determining whether the subject beinganalyzed maintained or thought they were maintaining a normal sleepingpattern prior to analysis, therefore the examples given above areincluded as exemplary rather than as a limitation, and those ways ofdetermining whether the subject maintained or thought they weremaintaining a normal sleeping pattern known to those skilled in the artare considered to be included in the present invention.

Various embodiments of the present invention include the step ofconducting an at-home sleep analysis that is attended from a remotelocation. Such remote attendance can be accomplished by an individual ina remote location (a remote monitor) periodically or continuouslyviewing the data transmitted from the in-home data acquisition system,including signals from the sensors applied to the subject, signals fromthe environmental sensors, and a pre-processed signal or signals basedat least in part on at least one of the sensors.

The preferred embodiment of secure data transmission that is compatiblewith HIPAA and HCFA guidelines will be implemented using a virtualprivate network. More preferably, the virtual private network will beimplemented using a specialized security appliance, such as the PIX506E, from Cisco Systems, Inc, capable of implementing IKE and IPSec VPNstandards using data encryption techniques such as 168-bit 3DES, 256-bitAES, and the like. Still more preferably, secure transmission will beprovided by a 3^(rd) party service provider or by the healthcarefacility's information technology department. The system will offerconfiguration management facilities to allow it to adapt to changingguidelines for protecting patient health information (PHI).

Preferably, the data includes a video channel. Preferably, the remotemonitor is capable of communicating with the subject, subject'sassistant, or other individual near the subject. Such communicationallows the remote monitor to provide instructions to the subject,subject's assistant, or other individual near the subject, for example,to adjust a sensor, close window blinds, remove a source of noise, orwake the subject. More preferably, the remote monitor is capable oftwo-way communication with the subject, subject's assistant, or otherindividual near the subject. Such communication allows the subject,subject's assistant, or other individual close to the subject to ask theremote monitor questions, for example, to clarify instructions.

Various embodiments of the present invention include the step ofapplying at least two sensors to the subject. The sensors can be appliedat any location. Preferably, the sensors are applied in a physician'soffice or place of business. The physician's place of business includesbut is not limited to an office building, a freestanding sleep center,location within a hospital, mobile vehicle or trailer, leased space, orsimilar location. Just as preferably, the sensors could be applied inthe subject's home or other sleeping location. The subject's sleepinglocation includes but is not limited to the subject's home, apartment,and the like, as well as a hotel, nursing facility, or other locationwhere an individual could sleep and where this analysis could be donemore controllably and/or less expensively than in a sleep lab orhospital setting. Similarly, the sensors can be applied by a variety ofindividuals, including but not limited to a physician, nurse, sleeptechnician, or other healthcare professional. Just as preferably, thesensors could be applied by the subject or the subject's spouse, friend,roommate, or other individual capable of attaching the various sensors.More preferably, the sensors could be applied by the subject or thesubject's spouse, friend, roommate, or other individual capable ofattaching the various sensors with guidance and instruction. Suchguidance and instruction can include static information such aspamphlets, audio recordings (on cassettes, compact discs, and the like),video recordings (on videocassettes, digital video discs, and the like),websites, and the like, as well as dynamic information such as directreal-time communication via telephone, cell phone, videoconference, andthe like.

The sensors that are used with various embodiments of the presentinvention are described herein but can also be any of those known tothose skilled in the art for the applications of this method. Thecollected physiological, kinetic, and environmental signals can beobtained by any method known in the art. Preferably, those sensorsinclude, but are not limited, to wet or dry electrodes, photodetectors,accelerometers, pneumotachometers, strain gauges, thermal sensors, pHsensors, chemical sensors, gas sensors (such as oxygen and carbondioxide sensors), transducers, piezo sensors, magnetometers, pressuresensors, static charge-sensitive beds, microphones, audio monitors,video monitors, and the like. The invention is envisioned to includethose sensors subsequently developed by those skilled in the art todetect these types of signals. For example, the sensors can be magneticsensors. Because electro-physiological signals are, in general,electrical currents that produce associated magnetic fields, the presentinvention further anticipates methods of sensing those magnetic fieldsto acquire the signal. For example, new magnetic sensors could collectbrain wave signals similar to those that can be obtained through atraditional electrode applied to the subject's scalp.

Various embodiments of the present invention include a step for applyingsensors to the subject. This step can be performed or accomplished in anumber of ways. In the simplest form, two sensors are applied to thesubject to measure a single channel of physiologic or kinetic data. In asomewhat more complex form, multiple sensors are applied to the subjectto collect data sufficient for a full PSG test. The preferred set ofsensors for PSG testing includes sensors for two EEG channels, one EOGchannels, one chin EMG channel, one nasal airflow channel, one oralairflow channel, one ECG channel, one thoracic respiratory effortchannel, one abdominal respiratory effort channel, one pulse oximetrychannel, and one shin or leg EMG channel. More preferably, the minimalset of PSG sensors is augmented with at least one additional channel ofEOG, one channel of body position (ex., an accelerometer), one channelof video, and optionally one channel of audio. In an even more complexform, many sensors are applied to the subject to collect full PSG dataas well as additional physiological, kinetic, and environmental data.For example, additional EEG electrodes may be applied to the subject torule out seizure disorders, an esophageal pH sensor may be used todetect acid reflux, and a hygrometer or photometer may be used to detectambient humidity or light, respectively. The set of sensors can be twosensors. More preferably, four sensors are used. Still more preferablyfive sensors; still more preferably seven sensors; still more preferablyten sensors; still more preferably twelve sensors; still more preferablyfifteen sensors; still more preferably twenty-four sensors.

Electro-physiological signals such as EEG, ECG, EMG, EOG,electroneurogram (ENG), electroretinogram (ERG), and the like can becollected via electrodes placed at one or several relevant locations onthe subject's body. For example when measuring brain wave or EEGsignals, electrodes may be placed at one or several locations on thesubject's scalp. In order to obtain a good electro-physiological signal,it is desirable to have low impedances for the electrodes. Typicalelectrodes placed on the skin may have an impedance in the range of from5 to 10 kΩ. It is in generally desirable to reduce such impedance levelsto below 2 kΩ. A conductive paste or gel may be applied to the electrodeto create a connection with an impedance below 2 kΩ. Alternatively or inconjunction with the conductive gel, a subject's skin may bemechanically abraded, the electrode may be amplified, or a dry electrodemay be used. Dry physiological recording electrodes of the typedescribed in U.S. Pat. No. 7,032,301 are herein incorporated byreference. Dry electrodes are advantageous because they use no gel thatcan dry out, skin abrasion or cleaning is unnecessary, and the electrodecan be applied in hairy areas such as the scalp. Additionally ifelectrodes are used as the sensors, preferably at least two electrodesare used for each channel of data—one signal electrode and one referenceelectrode. Optionally, a single reference electrode may be used for morethan one channel.

When electrodes are used to collect EEG or brain wave signals, commonlocations for the electrodes include frontal (F), parietal (P), mastoidprocess (A), central (C), and occipital (O). Preferably for the presentinvention, when electrodes are used to collect EEG or brain wave data,at least one electrode is placed in the occipital position andreferenced against an electrode placed on the mastoid process (A). Morepreferably, when electrodes are used to collect EEG or brain wave data,electrodes are placed to obtain a second channel of data from thecentral location. If further EEG or brain wave signal channels aredesired, the number of electrodes required will depend on whetherseparate reference electrodes or a single reference electrode is used.

If electrodes are used to collect cardiac signals using an ECG, they maybe placed at specific points on the subject's body. The ECG is used tomeasure the rate and regularity of heartbeats, determine the size andposition of the heart chambers assess any damage to the heart, anddiagnose sleeping disorders. An ECG is important as a tool to detect thecardiac abnormalities that can be associated with respiratory-relateddisorders.

As the heart undergoes depolarization and repolarization, electricalcurrents spread throughout the body because the body acts as a volumeconductor. The electrical currents generated by the heart are commonlymeasured by an array of twelve electrodes placed on the arms, legs, andchest. Although a full ECG test typically involves twelve electrodes,only two are required for many tests such as a sleep study. Whenelectrodes are used to collect ECG with the present invention,preferably only two electrodes are used. When two electrodes are used tocollect ECG, preferably one is placed on the subject's left-hand ribcageunder the armpit, and the other preferably on the right-hand shouldernear the clavicle bone. Optionally, a full set of twelve ECG electrodesmay be used, such as if the subject is suspected to have a cardiacdisorder. The specific location of each electrode on a subject's body iswell known to those skilled in the art and varies between bothindividuals and types of subjects. If electrodes are used to collectECG, preferably the electrode leads are connected to a device containedin the signal processing module of the in-home data acquisition systemused in the present invention that measures potential differencesbetween selected electrodes to produce ECG tracings.

The two basic types of ECG leads are bipolar and unipolar. Bipolar leads(standard limb leads) have a single positive and a single negativeelectrode between which electrical potentials are measured. Unipolarleads (augmented leads and chest leads) have a single positive recordingelectrode and use a combination of the other electrodes to serve as acomposite negative electrode. Either type of lead is acceptable forcollecting ECG signals in the present invention.

Other sensors can be used to measure various parameters of a subject'srespirations. Measurement of airflow is preferably measured usingsensors or devices such as a pneumotachometer, strain gauges, thermalsensors, transducers, piezo sensors, magnetometers, pressure sensors,static charge-sensitive beds, and the like. These sensors or devicesalso preferably measure nasal pressure, respiratory inductanceplethysmography, thoracic impedance, expired carbon dioxide, trachealsound, snore sound, blood pressure and the like. Measurement ofrespiratory effort is preferably measured by a respiration belt,esophageal pressure, surface diaphragmatic EMG, and the like.Measurement of oxygenation and ventilation is preferably measured bypulse oximetry, transcutaneous oxygen monitoring, transcutaneous carbondioxide monitoring, expired end carbon dioxide monitoring, and the like.

One example of such a sensor for measuring respirations either directlyor indirectly is a respiration belt. Respiration belts can be used tomeasure a subject's abdominal and/or thoracic expansion over ameasurement time period. The respiration belts may contain a straingauge, a pressure transducer, or other sensors that can indirectlymeasure a subject's respirations and the variability of respirations byproviding a signal that correlates to the thoracic/abdominalexpansion/contractions of the subject's thoracic/abdominal cavity. Ifrespiration belts are used, they may be placed at one or severallocations on the subject's torso or in any other manner known to thoseskilled in the art. Preferably, when respiration belts are used, theyare positioned below the axilla and/or at the level of the umbilicus tomeasure rib cage and abdominal excursions. More preferably, at least twobelts are used, with one positioned at the axilla and the other at theumbilicus.

Another example of a sensor or method for measuring respirations eitherdirectly or indirectly is a nasal cannula or a facemask used to measurethe subject's respiratory airflow. Nasal or oral airflow can be measuredquantitatively and directly with a pneumotachograph consisting of apressure transducer connected to either a standard oxygen nasal cannulaplaced in the nose or a facemask over the subject's mouth and nose.Airflow can be estimated by measuring nasal or oral airway pressure thatdecreases during inspiration and increases during expiration.Inspiration and expiration produce fluctuations on the pressuretransducer's signal that is proportional to airflow. A single pressuretransducer can be used to measure the combined oral and nasal airflow.Alternatively, the oral and nasal components of these measurements canbe acquired directly through the use of at least two pressuretransducers, one transducer for each component. Preferably, the pressuretransducer(s) are internal to the interface box. If two transducers areused for nasal and oral measurements, preferably each has a separate airport into the interface box.

Software filtering can obtain “snore signals” from a single pressuretransducer signal by extracting the high frequency portion of thetransducer signal. This method eliminates the need for a separatesensor, such as a microphone or another transducer, and also reduces thesystem resources required to detect both snore and airflow. A modifiednasal cannula or facemask connected to a carbon dioxide or oxygen sensormay be used to measure respective concentrations of these gases. Inaddition, a variety of other sensors can be connected with either anasal cannula or facemask to measure a subject's respirations directlyor indirectly.

Still another example of a sensor or method of directly or indirectlymeasuring respirations of the subject is a pulse oximeter. The pulseoximeter can measure the oxygenation of the subject's blood by producinga source of light at two wavelengths (650 nm and 905, 910, or 940 nm).Hemoglobin partially absorbs the light by amounts that differ dependingon whether it is saturated or desaturated with oxygen. Calculating theabsorption at the two wavelengths leads to an estimate of the proportionof oxygenated hemoglobin. Preferably, pulse oximeters are placed on asubject's earlobe or fingertip. More preferably, the pulse oximeter isplaced on the subject's index finger. In one embodiment of the presentinvention, a pulse oximeter is built-in or hard-wired to the interfacebox. Alternatively, the pulse oximeter can be a separate unit incommunication with either the interface box or the base station viaeither a wired or wireless connection.

Kinetic data can be obtained by accelerometers placed on the subject.Alternatively, several accelerometers can be placed in various locationson the subject, for example on the wrists, torso, and legs. Theseaccelerometers can provide both motion and general position/orientationdata by measuring gravity. A video signal can also provide some kineticdata after processing. Alternatively, stereo video signals can providethree-dimensional position and motion information. Kinetic data includesbut is not limited to frequent tossing and turning indicative of anunsuitable mattress, excessive movement of bedding indicating unsuitablesleeping temperatures, and unusual movement patterns indicating pain.

Environmental data can be collected by video cameras, microphones (todetect noise level, etc.), photodetectors, light meters, thermalsensors, particle detectors, chemical sensors, mold sensors, olfactorysensors, barometers, hygrometers, and the like. Environmental data canprovide insight into the subject's sleeping location and habits that isunavailable in the traditional laboratory setting. Environmental datacan indicate that the subject's sleeping location is a potential sourceof the subject's sleeping difficulty. By way of example, but notlimitation, environmental data can indicate that the subject's sleepinglocation has an unsuitable temperature, humidity, light level, noiselevel, or air quality. For example, these environmental conditions cancause sweating, shivering, sneezing, coughing, noise, and/or motion thatdisrupts the patient's sleep. The environmental sensors can be placedanywhere in the subject's sleeping location or on the subject, ifappropriate. Preferably, the environmental sensors are placed near, butnot necessarily on, the subject.

Other sensors can be used to measure various parameters of a subject'sphysiological, kinetic, or environmental conditions. These otherparameters are preferably measured using sensors or devices such as aphotodetectors, light meters, accelerometers, pneumotachometers, straingauges, thermal sensors, pH sensors, chemical sensors, transducers,piezo sensors, magnetometers, pressure sensors, static charge-sensitivebeds, audio monitors, microphones, reflective markers, video monitors,hygrometers, and the like. Because the system is programmable,potentially any transducer-type sensor that outputs an electrical signalcan be used with the system.

Various embodiments of the present invention include the step ofconnecting the applied sensors to an in-home data acquisition system.The sensors can be connected to the in-home data acquisition systemeither before or after they are applied to the subject. As an example ofconnecting the sensors to the in-home data acquisition system after thesensors are applied to the subject, a physician can apply the sensors tothe subject and then send the subject home. While at home, the subjectcan connect the applied sensors to the in-home data acquisition system.Alternatively, the sensors can be connected to the in-home dataacquisition system and then applied to the subject.

The sensors can be permanently hardwired to at least part of the in-homedata acquisition system. More preferably, the sensors are connected toat least part of the in-home data acquisition system via releasableconnector. The physiological sensors are generally hardwired(permanently or via releasable connector) to the in-home dataacquisition system, but the ongoing evolution in wireless sensortechnology may allow sensors to contain transmitters. Optionally, suchsensors are wirelessly connected to the in-home data acquisition system.As such, these sensors and the wireless connection method are consideredto be part of the present invention. With the advances inmicroelectromechanical systems (MEMS) sensor technology, the sensors mayhave integrated analog amplification, integrated A/D converters, andintegrated memory cells for calibration, allowing for some signalconditioning directly on the sensor before transmission.

Preferably, the sensors are all connected in the same way at the sametime, although this is certainly not required. It is possible, but lesspreferable, to connect the sensors with a combination of methods (i.e.,hardwired or wireless) at a combination of times (i.e., some beforeapplication to the subject, and some after application to the subject).

Various embodiments of the present invention use an in-home dataacquisition system. The in-home data acquisition system is preferablyportable. By portable, it is meant, among other things, that the deviceis capable of being transported relatively easily. Relative ease intransport means that the device is easily worn and carried, generally ina carrying case, to the point of use or application and then worn by thesubject without significantly affecting any range of motion.Furthermore, any components of the in-home data acquisition system thatare attached to or worn by the subject, such as the sensors and patientinterface box, should also be lightweight. Preferably, thesepatient-contacting components of the device (including the sensors andthe patient interface box) weigh less than about 10 lbs., morepreferably less than about 7.5 lbs., even more preferably less thanabout 5 lbs., and most preferably less than about 2.5 lbs. Thus, thepatient-contacting components of the device preferably arebattery-powered and use a data storage memory card and/or wirelesstransmission of data, allowing the subject to be untethered.Furthermore, the entire in-home data acquisition system (including thepatient-contacting components as well as any environmental sensors, basestation, or other components) preferably should be relativelylightweight. By relatively lightweight, it is meant preferably theentire in-home data acquisition system, including all components such asany processors, computers, video screens, cameras, and the likepreferably weigh less in total than about 20 lbs., more preferably lessthan about 15 lbs., and most preferably less than about 10 lbs. Thisin-home data acquisition system preferably can fit in a reasonably sizedcarrying case so the patient or assistant can easily transport thesystem. By being lightweight and compact, the device should gain greateracceptance for use by the subject.

While the equipment and methods used in the various embodiments of thepresent invention can be used in rooms or buildings adjacent to thesubject's sleeping location, due to the equipment's robust nature thesemethods are preferably performed over greater distances. Preferably, thesubject's sleeping location and the remote locations, for example thelocation of the remote monitor, are separate buildings. Preferably, thesubject's sleeping location is at least 1 mile from the remotelocation(s) receiving the data; more preferably, the subject's sleepinglocation is at least 5 miles from the remote location(s) receiving thedata; even more preferably, the subject's sleeping location is at leasttwenty miles from the remote location(s) receiving the data; still morepreferably, the subject's sleeping location is at least fifty miles fromthe remote location(s) receiving the data; still even more preferably,the subject's sleeping location is at least two hundred-fifty miles fromthe remote location(s) receiving the data; more preferably, thesubject's sleeping location is in a different state from the remotelocation(s) receiving the data; and most preferably, the subject'ssleeping location is in a different country from the remote location(s)receiving the data.

Various embodiments of the present invention use an in-home dataacquisition system capable of receiving signals from the sensors appliedto the subject and capable of retransmitting the signals or transmittinganother signal based at least in part on at least one of the signals. Inits simplest form, the in-home data acquisition system preferably shouldinterface with the sensors applied to the subject and retransmit thesignals from the sensors. Preferably, the in-home data acquisitionsystem wirelessly transmits the signals from the sensors. Optionally,the in-home data acquisition system also pre-processes the signals fromthe sensors and transmits the pre-processed signals. Further optionally,the data acquisition is also capable of storing the signals from thesensors and/or any pre-processed signals.

Optionally, the in-home data acquisition system can be a single boxcontaining a sensor interface module, a pre-processor module, and atransmitter module. Further optionally, the in-home data acquisitionsystem could consist of several boxes that communicate with each other,each box containing one or more modules. For example, the dataacquisition could consist of (a) a patient interface box containing asensor interface module, a pre-processor, a transmitter, and a receiver;and (b) a base station box containing a second pre-processor, atransmitter, and a receiver. In this example, the transmitter andreceiver of the patient box are used to communicate with the basestation box. The transmitter and receiver of the base station box areused to both communicate with the patient box and a remote monitoringstation, remote analysis station, remote data storage station, and thelike. Similarly, the data acquisition could consist of (a) a patientinterface box containing a sensor interface module, a transmitter, and areceiver; (b) a processor box containing a pre-processor, a transmitter,and a receiver; and (c) a base station box containing only a receiverand a transmitter. In these configurations, it is not necessary for thetransmitters to be of the same type. For example, the transmitter in thepatient interface box can be a wired or Bluetooth transmitter, and thetransmitter in the base station box can be a WiFi or IEEE 802.11transmitter designed to establish connections over larger distances.

Various embodiments of the present invention use an in-home dataacquisition system capable of storing and/or retransmitting the signalsfrom the sensors or storing and/or transmitting another signal based atleast in part on at least one of the signals. The in-home dataacquisition system can be programmed to send all signal data to theremovable memory, to transmit all data, or to both transmit all data andsend a copy of the data to the removable memory. When the in-home dataacquisition system is programmed to store a signal or pre-processedsignal, the signals from the sensors can be saved on a medium in orderto be retrieved and analyzed at a later date. Media on which data can besaved include, but are not limited to chart recorders, hard drive,floppy disks, computer networks, optical storage, solid-state memory,magnetic tape, punch cards, etc. Preferably, data are stored onremovable memory. For both storing and transmitting or retransmittingdata, flexible use of removable memory can either buffer signal data orstore the data for later transmission. Preferably, nonvolatile removablememory can be used to customize the system's buffering capacity andcompletely store the data.

If the in-home data acquisition system is configured to transmit thedata, the removable memory acts as a buffer. In this situation, if thein-home data acquisition system loses its connection with the receivingstation, the in-home data acquisition system will temporarily store thedata in the removable memory until the connection is restored and datatransmission can resume. If however the in-home data acquisition systemis configured to send all data to the removable memory for storage, thenthe system does not transmit any information at that time. In thissituation, the data stored on the removable memory can be retrieved byeither transmission from the in-home data acquisition system, or byremoving the memory for direct reading.

The method of directly reading will depend on the format of theremovable memory. Preferably the removable memory is easily removableand can be removed instantly or almost instantly without tools. Thememory is preferably in the form of a card and most preferably in theform of a small easily removable card with an imprint (or upper or lowersurface) area of less than about two sq. in. If the removable memory isbeing used for data storage, preferably it can write data as fast as itis produced by the system, and it possesses enough memory capacity forthe duration of the test. These demands will obviously depend on thetype of test being conducted, tests requiring more sensors, highersampling rates, and longer duration of testing will require faster writespeeds and larger data capacity. The type of removable memory used canbe almost any type that meets the needs of the test being applied. Someexamples of the possible types of memory that could be used include butare not limited to Flash Memory such as CompactFlash, SmartMedia,Miniature Card, SD/MMC, Memory Stick, or xD-Picture Card. Alternatively,a portable hard drive, CD-RW burner, DVD-RW burner or other data storageperipheral could be used. Preferably, a SD/MMC—flash memory card is useddue to its small size. A PCMCIA card is least preferable because of thesize and weight.

When the in-home data acquisition system is programmed to retransmit thesignals from the sensors, preferably the in-home data acquisition systemtransmits the signals to a processor for analysis. More preferably, thein-home data acquisition system immediately retransmits the signals to aprocessor for analysis. Optionally, the in-home data acquisition systemreceives the signals from one or more of the aforementioned sensors andstores the signals for later transmission and analysis. Optionally, thein-home data acquisition system both stores the signals and immediatelyretransmits the signals.

When the in-home data acquisition system is programmed to retransmit thesignals from the sensors or transmit a signal based at least in part onthe signal from the sensors (collectively “to transmit” in thissection), the in-home data acquisition system can transmit througheither a wireless system, a tethered system, or some combinationthereof. When the system is configured to transmit data, preferably thedata transmission step utilizes a two-way (bi-directional) datatransmission. Using two-way data transmission significantly increasesdata integrity. By transmitting redundant information, the receiver (theprocessor, monitoring station, or the like) can recognize errors andrequest a renewed transmission of the data. In the presence of excessivetransmission problems, such as transmission over excessive distances orobstacles absorbing the signals, the in-home data acquisition system cancontrol the data transmission or independently manipulate the data. Withcontrol of data transmission it is also possible to control or re-setthe parameters of the system, e.g., changing the transmission channel orencryption scheme. For example, if the signal transmitted issuperimposed by other sources of interference, the receiving componentcould secure a flawless transmission by changing the channel. Anotherexample would be if the transmitted signal is too weak, the receivingcomponent could transmit a command to increase the transmitting power.Still another example would be for the receiving component to change thedata format of the transmission, e.g., in order to increase theredundant information in the data flow. Increased redundancy allowseasier detection and correction of transmission errors. In this way,safe data transmissions are possible even with the poorest transmissionqualities. This technique opens a simple way to reduce the transmissionpower requirements, thereby reducing the energy requirements andproviding longer battery life. Another advantage of a bi-directionaldigital data transmission lies in the possibility of transmitting testcodes in order to filter out external interferences, for example,refraction or scatter from the transmission current. In this way, it ispossible to reconstruct falsely transmitted data.

Several preferable embodiments of this method employ a wireless in-homedata acquisition system. This wireless in-home data acquisition systemconsists of several components, each wirelessly connected. Data iscollected from the sensors described above by a patient interface box.The patient interface box then wirelessly transmits the data to aseparate signal pre-processing module, which then wirelessly transmitsthe pre-processed signal to a receiver. Alternatively, the patientinterface box processes the signal and then directly transmits theprocessed signal directly to the receiver using wireless technology.Further alternatively, the patient interface box wirelessly transmitsthe signals to the receiver, which then pre-processes the signal.Preferably, the wireless technology used by the in-home data acquisitionsystem components is radio frequency based. Most preferably, thewireless technology is digital radio frequency based. The signals fromthe sensors and/or the pre-processed signals are transmitted wirelesslyto a receiver, which can be a base station, a transceiver hooked to acomputer, a personal digital assistant (PDA), a cellular phone, awireless network, or the like. Most preferably, the physiologicalsignals are transmitted wirelessly in digital format to a receiver.

Wireless signals between the wireless in-home data acquisition systemcomponents are both received and transmitted via frequencies preferablyless than about 2.0 GHz. More preferably, the frequencies are primarily902-928 MHz, but Wireless Medical Telemetry Bands (WMTS), 608-614 MHz,1395-1400 MHz, or 1429-1432 MHz can also be used. The present inventionmay also use other less preferable frequencies above 2.0 GHz for datatransmission, including but not limited to such standards as Bluetooth,WiFi, IEEE 802.11, and the like.

When a component of the wireless in-home data acquisition system isconfigured to wirelessly transmit data, it is preferably capable ofconducting a RF sweep to detect an occupied frequency or possibleinterference. The system is capable of operating in either “manual” or“automatic” mode. In the manual mode, the system conducts an RF sweepand displays the results of the scan to the system monitor. The user ofthe system can then manually choose which frequency or channel to usefor data transmission. In automatic mode, the system conducts a RF sweepand automatically chooses which frequencies to use for datatransmission. The system also preferably employs a form of frequencyhopping to avoid interference and improve security. The system scans theRF environment then picks a channel over which to transmit based on theamount of interference occurring in the frequency range.

The receiver (base station, remote communication station, or the like)of various embodiments of the wireless in-home data acquisition systemcan be any device known to receive RF transmissions used by thoseskilled in the art to receive transmissions of data. By way of examplebut not limitation, the receiver can include a communications device forrelaying the transmission, a communications device for re-processing thetransmission, a communications device for re-processing the transmissionthen relaying it to another remote communication station, a computerwith wireless capabilities, a PDA with wireless capabilities, aprocessor, a processor with display capabilities, and combinations ofthese devices. Optionally, the receiver can further transmit data toanother device and/or back. Further optionally, two different receiverscan be used, one for receiving transmitted data and another for sendingdata. For example, with the wireless in-home data acquisition systemused in the present invention, the receiver can be a wireless routerthat establishes a broadband Internet connection and transmits thephysiological signal to a remote Internet site for analysis, preferablyby the subject's physician or another clinician. Other examples of areceiver are a PDA, computer, or cell phone that receives the datatransmission, optionally re-processes the information, and re-transmitsthe information via cell towers, land phone lines, or cable to a remoteprocessor or remote monitoring site for analysis. Other examples of areceiver are a computer or processor that receives the data transmissionand displays the data or records it on some recording medium that can bedisplayed or transferred for analysis at a later time.

Preferably, the in-home data acquisition system retransmits the signalsfrom the sensors applied to the subject or transmits a signal based atleast in part on at least one of the physiological, kinetic, orenvironmental signals at substantially a same time as the signal isreceived or generated. At substantially the same time preferably meanswithin approximately one hour. More preferably, at substantially thesame time means within thirty minutes. Still more preferably, atsubstantially the same time means within ten minutes. Still morepreferably, at substantially the same time means within approximatelyone minute. Still more preferably, at substantially the same time meanswithin milliseconds of when the signal is received or generated. Mostpreferably, a substantially same time means that the signal istransmitted or retransmitted at a nearly instantaneous time as it isreceived or generated. Transmitting or retransmitting the signal atsubstantially a same time allows the physician or monitoring service toreview the subject's physiological and kinetic signals and theenvironmental signals and if necessary to make a determination, whichcould include modifying the patient's treatment protocols or asking thesubject to adjust the sensors.

Various embodiments of the present invention include a step ofmonitoring a patient from a separate monitoring location. Datatransmitted in a remote monitoring application may include, but are notlimited to, physiological data, kinetic data, environmental data, audio,and/or video recording. It is preferable that both audio and videocommunications be components of the envisioned system in order toprovide interaction between patient and caregiver.

The envisioned remote monitoring step will require data processing,storage, and transmission. This step may be completed or accomplished inone or more modules of the in-home data acquisition system. Thepreferred embodiment realizes the remote system as two separatecomponents with a patient interface module that can collect, digitize,store, and transmit data to a base station module that can store,process, compress, encrypt, and transmit data to a remote monitoringlocation.

Preferably, the data is transmitted from a base station to a database orremote monitoring location with a wireless module or card through acellular service provider. The envisioned remote monitoring applicationmay allow for multiple remote monitoring locations anywhere in theworld. Remote data collection to monitoring station configurations mayinclude, but are not limited to one-to-one, one-to-many, many-to-one, ormany-to-many. The envisioned system may include a central server, orgroup of servers that can collect data from one or more remote sites andoffer delivery to multiple viewing clients.

It is preferable that the remote monitoring application employ awireless network link between the patient and caregiver such as acellular wireless network. Other wireless techniques include but are notlimited to satellite communications, direct radio, infrared links, andthe like. Data transmission through a wired network such as dial-upmodem, digital subscriber line (DSL), or fiber-optic, while lesspreferable, can also be used. Bandwidth management facilities will beemployed to facilitate remote monitoring in low-speed communicationnetworks. Several data compression techniques are envisioned to maximizesystem utilization in low-bandwidth environments.

Data compression using lossless encoding techniques can provide basicthroughput optimization, while certain lossy encoding techniques willoffer far greater throughput while still providing useful data. Lossyencoding techniques may include but are not limited to decimation, ortransmission of a compressed image of the data. The preferred method forencoding will include special processing from the transmitter that willpreprocess the data according to user-selectable options, such asdigital filtering, and take into the account the desired visualrepresentation of that information, such as pixel height and targetimage width. Facilities can be made within the system to control theencoding in order to optimize utilization on any given network. Controlover the encoding methods may include, but is not limited to selectionof a subset of the entire set of signals, target image size, anddecimation ratio.

Data encryption can be applied to secure data transmissions over anynetwork. Encryption methods may include but are not limited to simpleobfuscation and sophisticated ciphers.

The preferred embodiment of the aforementioned remote monitoring system(a form of the in-home data acquisition system) will consist of severalsystem modules. A patient interface module will collect physiologicaland kinetic data and transmit them to a base station module. The basestation module will receive the physiological and kinetic data from thepatient module, and will also directly connect to the environmentalsensors. The base station module will consist of an embedded computerequipped with a cellular wireless data/voice card and a night-visionvideo acquisition system. The embedded computer will collect, analyze,compress, and encrypt the data and relay them to one or more viewingcaregivers. The remote monitoring systems will broadcast theirdynamically assigned IP addresses to a dedicated address server, whichwill be used for lookup by the viewing caregivers. Computer softwareused by caregivers will enumerate each remote monitoring system in thefield using the aforementioned address server and allow caregivers toselect one or more for monitoring. The software will have the ability tocontrol data acquisition including start and stop of acquisition, aswell as system reconfiguration.

The software will also provide real-time control over the display ofdata including page width, amplitude, color, montage, and the like. Thesoftware will also provide both real-time video and audio communicationwith the patient using dual services from the cellular card. Video willpreferably be transmitted through the data connection, and audio willpreferably be transmitted through the voice connection.

Signal quality of the signals from all the sensors can be affected bythe posture and movement of the subject. For methods of the presentinvention, it is important to reduce motion artifacts from the sensorplacement. Errors in the form of noise can occur when biopotential dataacquisition is performed on a subject. For example, a motion artifact isnoise that is introduced to a biopotential signal via motion of anelectrode placed on the skin of a subject. A motion artifact can also becaused by bending of the electrical leads connected to any sensor. Thepresence of motion artifacts can result in misdiagnosis, prolongprocedure duration and can lead to delayed or inappropriate treatmentdecisions. Thus, it is imperative to remove motion artifact from thebiopotential signal to prevent these problems from occurring duringtreatment.

The present method of collecting signals from a subject includes a meansof reducing motion artifacts. Preferably, the electrode sensors are usedwith conductive gels or adhesives. More preferably, dry electrodes areused with or without conductive gels or adhesives. Still morepreferably, the device's firmware and/or software uses body motioninformation for artifact correction. Most preferably, a combination ofthe above methods is used.

The most common methods for reducing the effects of motion artifacts insensors such as electrodes have focused on skin deformation. Thesemethods include removing the upper epidermal layer of the skin byabrasion, puncturing the skin near the electrode, or measuring skinstretch at the electrode site. The methods for skin abrasion ensure goodelectrical contact between the electrode and the subject's skin. In thismethod, an abrasive pad is mechanically rotated on the skin to abradethe skin surface before electrode placement. Moreover, medicalelectrodes have been used with an abrading member to prepare the skinafter application of the electrode whereby an applicator gun rotates theabrading member. Methods of skin preparation that abrade the skin with abundle of fibers have also been disclosed. The methods discussed aboveprovide a light abrasion of the skin to reduce the electrical potentialand minimize the impedance of the skin, thereby reducing motionartifacts.

Skin abrasion methods can cause unnecessary subject discomfort, prolongprocedure preparation time and can vary based on operator experience.Furthermore, skin abrasions methods can lead to infection, and do notprovide an effective solution to long term monitoring. Dry physiologicalrecording electrodes could be used as an alternative to gel electrodes.Dry physiological recording electrodes of the type described in U.S.Pat. No. 7,032,301 are herein incorporated by reference. Dryphysiological electrodes do not require any of the skin abrasiontechniques mentioned above and are less likely to produce motionartifacts in general.

Although the above-mentioned methods reduce motion artifacts, they donot completely eliminate them. The invention preferably incorporates astep to more completely remove motion and other artifacts by firmwareand/or software correction that utilizes information collectedpreferably from a sensor or device to detect body motion, and morepreferably from an accelerometer. In certain embodiments of the presentinvention, a 3-D accelerometer is directly connected to the in-home dataacquisition system. The in-home data acquisition system receives signalinputs from the accelerometer and at least one set of otherphysiological or kinetic signals. The microprocessor applies particulartests and algorithms comparing the two signal sets to correct any motionartifacts that have occurred. The processor in one embodiment applies atime synchronization test, which compares the at least one set ofphysiological or kinetic signal data to the accelerometer signal datasynchronized in time to detect motion artifacts and then remove thoseartifacts. Alternatively, the processor may apply a more complicatedfrequency analysis. Frequency analysis preferably in the form of waveletanalysis can be applied to the accelerometer and at least one set ofphysiological or kinetic signals to yield artifact detection. Yetanother alternative is to create a neural net model to improve artifactdetection and rejection. This allows for the system to be taught overtime to detect and correct motion artifacts that typically occur duringa test study. The above examples are only examples of possibleembodiments of the present invention and are not limitations. Theaccelerometer data need not be analyzed before wireless transmission; itcould be transmitted analyzed by a base station, computer, or the likeafter transmission. As should be obvious to those skilled in the art, a2-D accelerometer or an appropriate array of accelerometers could alsobe used. Gyroscopes could be used as well for these purposes.

Sensors can be used to detect motion of the subject's body or a portionof the subject's body. The motion information can then be used to detectthe posture and movement of the subject and to correct for error in theform of noise or motion artifact in the other sensor channels. To detectmotion, various embodiments of the present invention include sensors,devices, and methods of determining the posture and movement of thesubject. This information can be used when analyzing the physiologicalsignals. The posture and movement of the subject is preferablydetermined by signals received from an accelerometer or an array of twoor more accelerometers. Accelerometers are known in the art and aresuitable for use as motion-monitoring units. Various other types ofsensors can be additionally or alternatively used to sense the criteria(e.g., vibration, force, speed, and direction) used in determiningmotion. For particularly low power designs, the one or more sensors usedcan be largely mechanical.

Body movement of the subject will result in a high amplitude signal fromthe accelerometer. The in-home data acquisition system can also monitorthe sensor signals for any indication that the subject has moved, forexample from a supine position to an upright position. For example, theintegrated velocity signal computed from the vertical accelerationcomponent of the sensor data can be used to determine that the subjecthas just stood up from a chair or sat up in bed. A sudden change in thevertical signal, particularly following a prolonged period with littleactivity while the subject is sleeping or resting, confirms that aposture-changing event occurred.

In addition, a video camera can be used to detect subject movement andposition, and the information then used to correct any artifacts thatmay have arisen from such movement. Preferably, the camera is a digitalcamera. More preferably, the camera is a wireless digital camera. Stillmore preferably, the camera is a wireless digital infrared camera.Preferably, the video acquired from the camera is processed so that thesubject's movement and position are isolated from other information inthe video. The movement and position data that are acquired from thevideo is then preferably analyzed by software algorithms. This analysiswill yield the information needed to make artifact corrections of thephysiological signals.

One specific embodiment of the present invention using video subjectmovement detection involves the use of specially marked electrodes. Theelectrodes can be any appropriate electrode known in the art. The onlychange to the electrode is that they preferably have predetermined highcontrast marks on them to make them more visible to the video camera.These marking could be manufactured into the electrodes or simply be asticker that is placed on the back of the electrodes. These markingsenable the video system to accurately distinguish the electrodes fromthe rest of the video image. Using the markers on each visibleelectrode, the system can calculate of the movement of each individualelectrode, thus allowing for more accurate artifact correction.

In another specific embodiment of the invention, the system can detectsubject movement by monitoring the actual movement of the subject'sbody. Software is applied to the video that first isolates the positionof the subject's body, including limbs, and then continues to monitorthe motion of the subject.

There are numerous advantages to using video over other means ofartifact detection and correction. Foremost, video allows for thecalculation of movement artifacts from each individual electrode withoutthe need for accelerometers. This makes the use of video very costeffective in relation to other available methods. The video also can beused in conjunction with the accelerometer data to correct for motionartifacts, thus increasing the precision and accuracy of the system'smotion artifact correction capabilities.

Various embodiments of the present invention include the step ofpre-processing the signals received from the sensors attached to thesubject. The processor or pre-processor of various embodiments of thepresent invention can be independent, a part of the interface box, or apart of the base station. Optionally, pre-processing can correctartifacts, derive a snore signal, filter a signal, or compress and/orencrypt the data for transmission, each as described above. Preferably,the preprocessing step corrects for artifacts present in the sensorsignals.

Various embodiments of the present invention include the step ofanalyzing the received signals to determine if the patient has asleeping disorder. This step can be performed or accomplished a numberof ways. In one form, a sleep technician or other trained individualscores the sleep test in accordance with Rechtschaffen and Kales (R&K)criteria. Another form uses a standard MSLT analysis. Still another forminvolves automatic or computer-assisted scoring of the data. Theanalysis step can include a full R&K score, or specific features can betargeted. For example, in cases of suspected sleep-related breathingdisorders, the analysis can focus on detecting and classifyingrespiratory events. Any analysis method used to diagnose sleepingdisorders (including but not limited to insomnia, excessive daytimesleepiness, parasomnias, restless leg syndrome, periodic limb movementdisorder, and sleep-disordered breathing such as apneas) based onphysiological and/or kinetic data collected while the subject attemptsto sleep is an appropriate means of completing this step. Analysis canalso include subjective information from the subject, such as thesubject's response to questions. Such questions include, but are notlimited to, standard subjective questionnaires such as the Epworth andStandford Sleepiness Scale, and asking if the subject slept well.

The analysis can occur after receipt of the entire data set. Morepreferably, the analysis can take place in near-real time as the dataare received. Still more preferably, the analysis is computer-assistedand takes place in near-real time. Alternatively, the data can bepartially analyzed, with or without computer assistance, in near-realtime, and then fully analyzed at a later time. If at least some of theanalysis is conducted in near-real time with computer assistance, theanalysis software can provide an alert signal to draw attention to aphysiological or technological event. Physiological events include, butare not limited to, changes in blood oxygen saturation, changes inpulse, changes in sleep stage, and subject movement, such as leaving thebed. Technological events include, but are not limited to, movement of asensor, changes in electrode impedance, or loss of data. Once alerted toa physiological or technological event, the remote monitor can takeaction, including but not limited to communicating with the subject toaddress a problem, making a note of the event, conducting more detailedanalysis, altering the test parameters, or alerting another individualsuch as a physician, nurse, sleep technician, or the subject'sassistant.

Various embodiments of the present invention include the step ofevaluating the received signals to determine if they are adequate forlater analysis. This step can be performed or accomplished a number ofways. In the simplest form, the signal can be evaluated once just priorto the start of the sleep study. In another form, the signal isevaluated periodically during the study to determine its quality.Preferably, the signal(s) are evaluated both at the start of the studyand periodically during the study. Most preferably, the signals areevaluated at the beginning of the study and continuously during thestudy. If the signals are evaluated for adequacy, preferably the subjectcan be contacted to adjust the sensor as necessary. In this way,corrective action can adjust an inadequate signal to increase the valueof the sleep study data and enable later analysis.

By transmitting the data wirelessly in this application it is meant thatthe data at least in part of the data transfer process is transmittedwirelessly. This means for example that the data may be transmittedwirelessly from the patient data acquisition box to the base station andthen sent via wireless cellular card, internet, through the testingfacilities LAN, or any other communication system. This also means forexample that the data may be transmitted directly from the patient dataacquisition box through a wireless cellular card then over the internetto a database which distributes the data over a hardwired system to thesleep unit or lab. This also means for example that the data may betransmitted directly from the patient data acquisition box with awireless WIFI card directly to a wireless network then over the internetto a processor which retransmits the processed data to the sleep unit orlaboratory. Preferably, the patient data acquisition box, however, needsto wirelessly transmit the data. This allows for a simplified patienthookup and improved patient mobility.

The data collected for the sleep analysis conducted under the variousmethods of the present invention can be viewed by any number of medicalpersonnel and the patient themselves, if appropriate. Preferably, thedata is available to a sleep technician, to a doctor making theanalysis/diagnosis based on the data, and others involved in thesemethods. This data can be reviewed at multiple locations including butnot limited to the doctor's home or office, or anywhere else the doctoror other individuals associated with the analysis/diagnosis have accessto the internet or a intranet.

FIG. 1 is a block diagram of one embodiment of the sleep analysis methodof the present invention showing, among other things, the steps ofchecking the adequacy of signals and communicating with the subject. Inthis embodiment, a physician, nurse, technician, or the like appliessensors to the subject 2 at the physician's office or place of business.The subject is sent home 4 with an in-home data acquisition system. Athome, the subject or the subject's assistant connects the sensors to thein-home data acquisition system 6. The in-home data acquisition systemcollects some data from the sensors and transmits the data to a remotestation 8. At the remote station, a remote monitor checks the signalsfor adequacy 10. If the signal is not adequate for later analysis 12,the remote monitor communicates with the subject to adjust the sensor14. After the subject adjusts the sensor as instructed by the remotemonitor, the in-home data acquisition system collects and transmits moredata to the remote monitoring station 8. The signal from the adjustedsensor is checked for adequacy 10. The signal check loop 8, 10, 12, 14is repeated until the signals from the sensors are adequate for lateranalysis.

After the in-home data acquisition system is sending adequate signals12, the sleep test is started by collecting data while the subjectattempts to sleep at home 16. During the test, data is collected andtransmitted to the remote monitoring station 18. Based on thetransmitted data, a sleep analysis is performed and the patient isdiagnosed 20.

FIG. 2 is a signal flow diagram of one embodiment of the data flowthrough the wireless in-home data acquisition system used in certainembodiments of the present invention. The sensors generate physiologicalsignals 22, kinetic signals 24, and environmental signals 26. The sensorsignals 27 interface with the wireless in-home data acquisition system50, consisting of (a) a patient interface box 35 containing a sensorinterface module 28, a preprocessor module 30, a transceiver module 32,and a power module 34, and (b) a base station 43 containing a storagemodule 38, a second pre-processor module 40, and a communication module42. Typically, the patient interface box 35 is worn by the subjectduring the test period. For portability of the patient interface box 35,the power module 34 can be battery-based. The patient interface box 35sends data via wireless signal 46 to the base station 43. The basestation 43 uses the communication module 42 to retransmit the signalsfrom the sensors 27 and/or transmit signals based at least in part on atleast one of the signals 27 to remote stations (not shown). Optionally,environmental signals 26 could be fed directly into the base station 43.Further optionally, all the signals 27 could be fed directly into asingle box (not shown) containing the sensor interface module 28,pre-processor module 30, storage module 38, communication module 42, andpower module 34. Although transmission between the patient interface box35 and the base station box 43 is shown in FIG. 2 as wireless 46, theconnection could also be wired in other embodiments of the in-home dataacquisition system.

FIG. 3 is schematic of the remote data acquisition device and system ofthe present invention. In FIG. 3, a wireless in-home data acquisitionsystem 50 (shown in FIG. 2) is used to receive, filter, and optionallyanalyze signals 27 (shown in FIG. 2) from sensors (not shown) on asubject (not shown). The wireless in-home data acquisition system 50transmits a signal based, at least in part, on one or more of thesignals from the sensors on the subject. The in-home data acquisitionsystem 50 transmits a signal 55 preferably in real time from thesubject's home 52 to a server 70 for analysis. The signal 55 istransmitted over the internet or other communication system 58. Suchother communication systems include satellites, cellular networks, localarea networks (LAN), other wide area networks (WAN), or othertelecommunications system. If the signal 55 is transmitted over theinternet 58, preferably the signal 55 is transmitted using a cellularcard provided by cellular providers such as for example Sprint,Cingular, AT&T, T-Mobile, Alltel, Verizon or the like. The signal 55that is transmitted over the internet or other communication system 58can be compressed to provide better resolution or greater efficiency.The server 70 performs data analysis (not shown). The analyzed data 73is then entered into a database 76. The analyzed data 73 in the database76 is then accessible and can be requested 79 and sent to multiplereview stations 82 anywhere in the world via the internet or othercommunications system 58 for further analysis and review by clinicians,technicians, researchers, doctors and the like. The communicationssystems used for data transmission need not be the same at all stages.For example, the a cellular network can be used to transmit data betweenthe subject's home 52 and the remote analysis server 70. Then theinternet can be used to transmit data between the remote analysis server70 and the database 76. Finally in this example, a LAN can be used totransmit data between the database 76 and a review station 82.

FIG. 4 shows a diagram outlining the wireless in-home data acquisitionsystem in more detail. In FIG. 4, a patient interface box 85 receivessignal (not shown) from a sensor 91. This sensor 91 can be an EEGelectrode (as shown) or any of the other sensors described herein orknown in the art. Although one type of sensor 91 is shown, the patientinterface box 85 is capable of accepting multiple signals from multiplesensors 91. In a very simple embodiment of the present invention, thepatient interface box 85 generates a wireless signal 94 encoded withdata corresponding to the signal from the sensor 91. The patientinterface box 85 transmits the wireless signal 94 to base station 97. InFIG. 4, the wireless signal 94 is shown as radio frequency (RF). In thiscase, the patient interface box 85 generates a radio frequency signal 94by frequency modulating a frequency carrier and transmits the radiofrequency signal through module antenna 100. The base station 97receives the radio frequency signal 94 through base antenna 103,demodulates the radio frequency signal 94, and decodes the data. It isunderstood that other wireless means can be utilized with the presentinvention, such as infrared and optical, for example. RF wirelesstransmission is preferred. Although one module antenna 100 and one baseantenna 103 are shown in this embodiment, it is understood that two ormore types of antennas can be used and are included in the presentinvention. An external programming means 106, shown in FIG. 4 as apersonal computer, contains software that is used to program the patientinterface box 85 and the base station 97 through data interface cable109. The data interface cable 109 is connected to the base station 97 byconnector 112. Instead of a data interface cable 109, the patientinterface box 85 and the base station 97 can be programmed by radiofrequency (or other type) of signals transmitted between an externalprogramming means 106 and a base station 97 and the patient interfacebox 85 or to another base station 97. RF signals, therefore, can be bothtransmitted and received by both patient interface box 85 and basestation 97. In this event the patient interface box 85 also includes amodule receiver 133 (shown on FIG. 5) while the base station 97 alsoincludes a base transmitter 84, in effect making both the patientinterface box 85 and the base station 97 into transceivers. In addition,the data interface cable 109 also can be used to convey data from thebase station 97 to the external programming means 106. If a personalcomputer is the external programming means 106, it can monitor, analyze,and display the data in addition to its programming functions. The basereceiver 80 and module receiver 133 (shown on FIG. 5) can be anyappropriate receivers, such as direct or single conversion types. Thebase receiver 80 preferably is a double conversion superheterodynereceiver while the module receiver 133 (shown on FIG. 5) preferably is asingle conversion receiver. Advantageously, the receiver employed willhave automatic frequency control to facilitate accurate and consistenttuning of the radio frequency signal 94 received thereby.

Referring now to FIG. 5, there is shown a block diagram of the signalprocessing module 85 with the sensor 91 and the module antenna 100. Thesignal processing module 85 comprises input means 115, analog-to-digital(A/D) means 118, a module microcontroller 121 with a nonvolatile memory,advantageously, an EEPROM 124, a module transmitter 127, a connection toremovable memory 130, a module receiver 133 and a module power supply136. Although the module antenna 100 is shown externally located fromthe signal processing module 85, it can also be incorporated therein.The module antenna 100 may be a printed spiral antenna printed on acircuit board or on the case of the signal processing module 85 or othertype of antenna. A module power supply 136 provides electrical power tothe signal processing module 85 which includes the input means 115, A/Dmeans 118, module microcontroller 121, module transmitter 127 and modulereceiver 133. Additionally the signal processing module 85 willpreferably contain an accelerometer connected to a microprocessor 139for position detection, motion detection, and motion artifactcorrection.

The input means 115 is adjustable either under control of the modulemicrocontroller 121 or by means of individually populatable componentsbased upon the specific external input 88 (i.e. signal from any sensor)characteristics and range enabling the input means 115 to accept thatspecific external input 88. For example, if the input is a 4-20 mAanalog signal, the input means 88 is programmed by the modulemicrocontroller 121 and/or populated with the components needed toaccept that range and characteristic of signals. If the inputcharacteristics change the programming and/or components changeaccordingly but the same platform circuit board design is utilized. Inother words, the same platform design is utilized notwithstanding thecharacter, range, or quantity (i.e. number of external inputs 88) [up toa predetermined limit] of the input. For example, bioelectric signalssuch as EEG, EMG, EKG, EOG, or the like have typical amplitudes of a fewmicrovolts up to a few tens of millivolts. For a given application, aspecific frequency band of interest might be from 0.1 Hz to 100 Hz,whereas another application may require measurement of signals from 20Hz to 10 kHz. Alternatively, measurement of vital signs such as bodytemperature and respiration rate may deal with signals in a range of +5volts, with a frequency content from DC (0 Hz) to 20 Hz. For othermedical applications, the information of interest may be contained inthe signal as a current, current loop sensor, or it may take the form ofresistance, impedance, capacitance, inductance, conductivity, or someother parameter. The present invention anticipates using a single devicefor measuring such widely disparate signal types and presents distincteconomic advantages, especially to small enterprises such as a medicalclinic located in a rural area, which would be empowered by thisinvention to conduct tests that would otherwise require the patienttravel to a large medical center, with all the attendant cost thereof.

A single system possesses these capabilities due to the selectivelyadaptable input means 115 and A/D means 118, the frequency-agile moduletransmitter 127 and base transmitter 116, and the programmable modulemicrocontroller 121 and EEPROM 124. One universal platform design thencan be utilized for all applications. In addition, the signal processingmodule 85 can comprise multiple copies of the input means 115 and theA/D means 118. Cost savings can be achieved by multiplexing at severaldifferent points in the input means 115 and the A/D means 118 allowinghardware to be shared among external inputs 88.

After receipt by the input means 115, the external input 88 is inputtedto the A/D means 118. The A/D means 118 converts the input to a digitalsignal 142 and conditions it. The A/D means 118 utilizes at least oneprogrammable A/D converter. This programmable A/D converter may be anAD7714 as manufactured by Analog Devices or similar. Depending upon theapplication, the input means 115 may also include at least one low noisedifferential preamp. This preamp may be an INA126 as manufactured byBurr-Brown or similar. The module microcontroller 121 can be programmedto control the input means 115 and the A/D means 118 to provide specificnumber of external inputs 88, sampling rate, filtering and gain. Theseparameters are initially configured by programming the modulemicrocontroller 121 to control the input means 115 and the A/D means 118via input communications line 145 and A/D communications line 148 basedupon the input characteristics and the particular application. Ifdifferent sensors are used, the A/D converter is reconfigured byreprogramming the module microcontroller 121. In this manner, the inputmeans 115 and the A/D means 118 can be configured to accept analoginputs of 4-20 mA, +/−5 volts, +/−15 volts or a range from +/−microvoltsto millivolts. They also can be configured to accept digital inputs fordigital applications such as detection of contact closure.

The module microcontroller 121 controls the operation of the signalprocessing module 85. In the present invention, the modulemicrocontroller 121 includes a serial EEPROM 124 but any nonvolatilememory (or volatile memory if the signal processing module remainspowered) can be used. The EEPROM 124 can also be a separate componentexternal to the module microcontroller 121. Advantageously, the modulemicrocontroller 121 may be PIC16C74A PIC16C74B or a PIC16C77 bothmanufactured by MicroChip, or an Amtel AT90S8515 or similar. The modulemicrocontroller may advantageously contain two microprocessors in seriesas shown in FIG. 5. The module microcontroller 121 is programmed by theexternal programming means 106 (shown in FIG. 4) through the connector172 or through radio frequency signal from the base station 97 (shown inFIG. 4). The same module microcontroller 121, therefore, can be utilizedfor all applications and inputs by programming it for those applicationsand inputs. If the application or inputs change, the modulemicrocontroller 121 is modified by merely reprogramming. The digitalsignal 142 is inputted to the module microcontroller 121. The modulemicrocontroller 121 formats the digital signal 142 into a digital datastream 151 encoded with the data from the digital signal 142. Thedigital data stream 151 is composed of data bytes corresponding to theencoded data and additional data bytes to provide error correction andhousekeeping functions. Advantageously, the digital data stream 151 isorganized in data packets with the appropriate error correction databytes coordinated on a per data packet basis. These packets canincorporate data from a single input channel or from several inputchannels in a single packet, or for some applications may advantageouslyinclude several temporally differing measurements of one or a pluralityof input channels in a single packet. The digital data stream 151 isused to modulate the carrier frequency generated by the transmitter 127.

The module transmitter 127 is under module microcontroller 121 control.The module transmitter 127 employs frequency synthesis to generate thecarrier frequency. In the preferred embodiment, this frequency synthesisis accomplished by a voltage controlled crystal reference oscillator anda voltage controlled oscillator in a phase lock loop circuit. Thedigital data stream 151 is used to frequency modulate the carrierfrequency resulting in the radio frequency signal 94 which is thentransmitted through the module antenna 100. The generation of thecarrier frequency is controlled by the module microcontroller 121through programming in the EEPROM 124, making the module transmitter 127frequency agile over a broad frequency spectrum. In the United Statesand Canada a preferred operating band for the carrier frequency is 902to 928 MHz. The EEPROM 124 can be programmed such that the modulemicrocontroller 121 can instruct the module transmitter 127 to generatea carrier frequency in increments between 902 to 928 MHz. as small asabout 5 to 10 kHz. In the US and other countries of the world, thecarrier frequency may be in the 902-928 MHz, Wireless Medical TelemetryBands (WMTS), 608-614 MHz, 1395-1400 MHz, or 1429-1432 MHz or otherauthorized band. This allows the system to be usable in non-NorthAmerican applications and provides additional flexibility.

The voltage controlled crystal oscillator (not shown) in the moduletransmitter 127, not only provides the reference frequency for themodule transmitter 127 but, advantageously also provides the clockfunction 154 for the module microcontroller 121 and the A/D means 118assuring that all components of the signal processing module 85 aresynchronized. An alternate design can use a plurality of referencefrequency sources where this arrangement can provide certain advantagessuch as size or power consumption in the implementation.

The module receiver 133 in the signal processing module 85 receives RFsignals from the base station 97 (shown in FIG. 4). The signals from thebase station 97 can be used to operate and control the signal processingmodule 85 by programming and reprogramming the module microprocessor 121and EEPROM 124 therein.

Referring now to FIG. 6, the base station 97 has a base antenna 103through which RF signals 94 are received. Base microcontroller 160controls the operation of the base station 97 including base receiver163, base transmitter 166, and base power supply 169. Base receiver 163receives the RF signal 94 from base antenna 103. The base receiver 163demodulates the RF signal 94 and the base microcontroller 160 removesany error correction and performs other housekeeping tasks. The data isthen downloaded through connector 112 to the external programming means106 (shown in FIG. 4) or other personal computer (PC) or datastorage/viewing device for viewing in real time, storage, or analysis,or is downloaded to removable memory of some form.

FIG. 7 is a schematic diagram of a multi-task monitoring system. In FIG.7, a patient or subject is shown having the neurological 200, cardiac202, muscular 204, and other environmental conditions 206 measured bysensors (not shown) and input into four separate data acquisition units210, 212, 214, and 216. In this example, each unit 210, 212, 214, and216 can accept up to 32 inputs. The units transmit signals 220, 222,224, and 226 at different wireless radio frequencies from theirrespective antennas 228. The signals 220, 222, 224, and 226 do notinterfere with each other because they have been manually orautomatically selected to reduce interference as described earlier inthe application. The signals can be received 232 simultaneously or insome ordered fashion by the antenna 230 on the receiving unit 234. Thereceiving unit 234 is both data and electrically connected via a USBconnection 236 to a main processor or computer 238. The physiologicalsignals are then processed or further processed by the computer 238,depending on whether processing took place in the data acquisition units210, 212, 214, and 216. The information or data from the computer 238can be output to a monitor 240 and/or into a data file 242.

FIG. 8 is a diagram of an artifact rejection module 250 that can be usedin either the in-home data acquisition system (not shown) or a computeror processor (not shown) linked to the data acquisition unit of thepresent invention. In FIG. 8, a subject's EEG signal 252 is preferablycontinuously fed 254 into artifact rejection algorithms within the dataacquisition unit processor. Simultaneously sensor signals 260 from thesubject's movement or motion are also fed into the artifact rejectionprocessor so the EEG signal can be corrected 262 for effects of abnormalor prejudicial motion by the subject. The sensors for determining thesubject's motion are described above, but the most preferred is anaccelerometer that is incorporated into the EEG data acquisition unititself.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the present inventionwithout departing from the spirit and scope of the invention. Thus, itis intended that the present invention cover the modifications andvariations of this invention provided they come within the scope of theappended claims and their equivalents.

What we claim is:
 1. A system for conducting a home sleep analysis of asubject, the system comprising: a snore sensor configured to be appliedto the subject's torso, and/or nasal cannula or facemask, the snoresensor, and/or nasal cannula or facemask being configured to be worn byand/or applied to the subject; a respiratory effort sensor or belt, therespiratory effort sensor or belt being configured to be applied to thesubject's torso for measuring respiratory effort of the subject; afingertip pulse oximeter, the fingertip pulse oximeter being configuredto be applied to a fingertip of the subject to measure blood oxygenationof the subject; a kinetic sensor configured for measuring the subject'sbody position; and a patient interface box configured to be worn by thesubject while the subject sleeps in the subject's home, the portableinterface box being configured to be connected to at least: (i) thesnore sensor and/or nasal cannula or facemask; (ii) the respiratoryeffort sensor or belt; and (iii) the fingertip pulse oximeter; whereinthe patient interface box: a. comprises: i. a first processor, ii. amemory, iii. a transceiver or a transmitter, iv. a battery, v. a firstpressure transducer, vi. a first air port adapted for connecting thenasal cannula or facemask to the first pressure transducer, vii. asecond pressure transducer, and viii. a second air port adapted forconnecting the respiratory effort belt to the second pressuretransducer, and b. is configured to: i. obtain airflow data and/or snoredata, the snore and/or airflow data being based on an output of thesnore sensor and/or a sensor for directly or indirectly measuringairflow from the nasal cannula or facemask; ii. obtain respiratoryeffort data, the respiratory effort data being based on the respiratoryeffort sensor or belt; iii. obtain blood oxygenation data, the bloodoxygenation data being based on an output from the fingertip pulseoximeter; iv. obtain body position data, the body position data beingbased on an output from the kinetic sensor; and v. transmit with thetransceiver or the transmitter the obtained data of snore and/or airflowdata, respiratory effort data, blood oxygenation data, and body positiondata or related data to a remote database for analysis by a softwarestored on a tangible medium and executable by a second processor that,when executed, is configured to: a) based on one or more of the snoreand/or airflow data, respiratory effort data, blood oxygenation data,and body position data, identify one or more physiological ortechnological events indicative of a sleeping disorder; and b) output: 1) one or more of the airflow data, snore data, respiratory effortdata, blood oxygenation data, and body position data, and/or  2) theidentified physiological and technological events, to facilitate adetermination as to whether the subject suffers from a sleepingdisorder.
 2. The system in claim 1, wherein the software furtherincludes an algorithm adapted for identifying changes in sleep stagesand calculating a respiratory disturbance index using the obtained andtransferred data prior to medical diagnosis.
 3. The system in claim 2,wherein the remote database is adapted to collect information todetermine whether the subject being analyzed for a sleep disorder hasmaintained a normal sleeping pattern prior to analysis based onsubjective input from the subject or polysomnography data.
 4. The systemin claim 3, wherein the transceiver is further adapted to transfer theobtained data from the memory via cellular systems, Internet, satellite,wired-network and/or land lines to the remote database.
 5. The system inclaim 4, wherein the software is adapted to at least in part remove oridentify movement artifacts in the obtained data prior to analysis ofthe collected data by the software by comparing signals from the kineticsensor with at least one other kinetic or physiological signal toidentify and/or remove movement artifacts identified from the signals.6. The system in claim 5, wherein the software is adapted to furtherperform an automatic scoring of the obtained data to determine whetherthe subject suffers from a sleeping disorder.
 7. The system in claim 6,wherein the fingertip pulse oximeter is releasably connected to thepatient interface box.
 8. The system in claim 7, wherein the snore ismeasured and/or derived using a pressure sensor or a microphone.
 9. Thesystem in claim 1, wherein the software is adapted to at least in partremove or identify movement artifacts in the obtained data prior toanalysis of the collected data by the software by comparing signals fromthe kinetic sensor with at least one other kinetic or physiologicalsignal to identify and/or remove movement artifacts identified from thesignals.
 10. The system in claim 9, wherein the software furtherincludes an algorithm adapted for identifying changes in sleep stagesand calculating a respiratory disturbance index using the obtained andtransferred data prior to medical diagnosis.
 11. The system in claim 10,wherein the transceiver is further adapted to transfer the obtained datafrom the memory via cellular systems, Internet, satellite, wired-networkand/or land lines to the remote database.
 12. The system in claim 11,wherein the remote database is adapted to collect information todetermine whether the subject being analyzed for a sleep disorder hasmaintained a normal sleeping pattern prior to analysis based onsubjective input from the subject or polysomnography data.
 13. Thesystem in claim 12, wherein the fingertip pulse oximeter is releasablyconnected to the patient interface box.
 14. The system in claim 13,wherein the software is adapted to further perform an automatic scoringof the obtained data to determine whether the subject suffers from asleeping disorder.
 15. The system in claim 9, wherein the respiratoryeffort belt and the fingertip pulse oximeter are releasably connected tothe patient interface box.
 16. The system in claim 1, wherein thetransceiver is further adapted to transfer the obtained data from thememory via cellular systems, Internet, satellite, wired-network and/orland lines to the remote database.
 17. The system in claim 16, whereinthe software further includes an algorithm adapted for identifyingchanges in sleep stages and calculating a respiratory disturbance indexusing the obtained and transferred data prior to medical diagnosis. 18.The system in claim 17, wherein the remote database is adapted tocollect information to determine whether the subject being analyzed fora sleep disorder has maintained a normal sleeping pattern prior toanalysis based on subjective input from the subject or polysomnographydata.
 19. The system in claim 18, wherein the software is adapted to atleast in part remove or identify movement artifacts in the obtained dataprior to analysis of the collected data by the software by comparingsignals from the kinetic sensor with at least one other kinetic orphysiological signal to identify and/or remove movement artifactsidentified from the signals.
 20. The system in claim 19, wherein thesoftware is adapted to further perform an automatic scoring of theobtained data to determine whether the subject suffers from a sleepingdisorder.